Towards Odor-Sensitive Mobile Robots

J. Monroy, J. Gonzalez-Jimenez, "Towards Odor-Sensitive Mobile Robots", Electronic Nose Technologies and Advances in Machine Olfaction, IGI Global, pp. 244--263, 2018, doi:10.4018/978-1-5225-3862-2.ch012 Versión preprint, con permiso del editorOut of all the components of a mobile robot, its sensorial system is undoubtedly among the most critical ones when operating in real environments. Until now, these sensorial systems mostly relied on range sensors (laser scanner, sonar, active triangulation) and cameras. While electronic noses have barely been employed, they can provide a complementary sensory information, vital for some applications, as with humans. This chapter analyzes the motivation of providing a robot with gas-sensing capabilities and also reviews some of the hurdles that are preventing smell from achieving the importance of other sensing modalities in robotics. The achievements made so far are reviewed to illustrate the current status on the three main fields within robotics olfaction: the classification of volatile substances, the spatial estimation of the gas dispersion from sparse measurements, and the localization of the gas source within a known environment

Real-Time odor classification through sequential bayesian filtering

The classification of volatiles substances with an e-nose is still a challenging problem, particularly when working under real-time, out-of-the-lab environmental conditions where the chaotic and highly dynamic characteristics of the gas transportation induce an almost permanent transient state in the e-nose readings. In this work, a sequential Bayesian filtering approach is proposed to efficiently integrate information from previous e-nose observations while updating the belief about the gas class on a real-time basis. We validate our proposal with two real olfaction datasets composed of dynamic time-series experiments (gas transitions are Considered, but no mixture of gases), showing an improvement in the classification rate when compared to a stand-alone probabilistic classifier.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Gas Source Localization Strategies for Teleoperated Mobile Robots. An Experimental Analysis

Gas source localization (GSL) is one of the most important and direct applications of a gas sensitive mobile robot, and consists in searching for one or multiple volatile emission sources with a mobile robot that has improved sensing capabilities (i.e. olfaction, wind flow, etc.). This work adresses GSL by employing a teleoperated mobile robot, and focuses on which search strategy is the most suitable for this teleoperated approach. Four different search strategies, namely chemotaxis, anemotaxis, gas-mapping, and visual-aided search, are analyzed and evaluated according to a set of proposed indicators (e.g. accuracy, efficiency, success rate, etc.) to determine the most suitable one for a human-teleoperated mobile robot. Experimental validation is carried out employing a large dataset composed of over 150 trials where volunteer operators had to locate a gas-leak in a virtual environment under various and realistic environmental conditions (i.e. different wind flow patterns and gas source locations). We report different findings, from which we highlight that, against intuition, visual-aided search is not always the best strategy, but depends on the environmental conditions and the operator’s ability to understand how gas distributes.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach

In this paper we present a fast and precise method to estimate the planar motion of a lidar from consecutive range scans. For every scanned point we formulate the range flow constraint equation in terms of the sensor velocity, and minimize a robust function of the resulting geometric constraints to obtain the motion estimate. Conversely to traditional approaches, this method does not search for correspondences but performs dense scan alignment based on the scan gradients, in the fashion of dense 3D visual odometry. The minimization problem is solved in a coarse-to-fine scheme to cope with large displacements, and a smooth filter based on the covariance of the estimate is employed to handle uncertainty in unconstraint scenarios (e.g. corridors). Simulated and real experiments have been performed to compare our approach with two prominent scan matchers and with wheel odometry. Quantitative and qualitative results demonstrate the superior performance of our approach which, along with its very low computational cost (0.9 milliseconds on a single CPU core), makes it suitable for those robotic applications that require planar odometry. For this purpose, we also provide the code so that the robotics community can benefit from it.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish Government under project DPI2014-55826-R and the grant program FPI-MICINN 2012

Probabilistic localization of gas emission areas with a mobile robot in indoor environments

This work deals with the problem of gas source localization by a mobile robot with gas-sensing capabilities. Particularly, we address the problem for the case of indoor environments, where the presence of obstacles and the possibly complex structure with multiple rooms, inlets and outlets provoke the chaotic dispersion of the gases. Under these challenging conditions, where traditional approaches based on tracking or mathematical modeling of the plume cannot be applied, we propose a two-stage methodology to split the search into coarse and fine localization. Focusing on the broad localization, we contribute with a novel approach to estimate, from a set of sparse observations, the likelihood of different regions in the environment to hold a gas source. Experiments demonstrate that our approach is suitable to locate gas emission sources.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

An evaluation of plume tracking as a strategy for gas source localization in turbulent wind flows

Gas source localization is likely the most direct application of a mobile robot endowed with gas sensing capabilities. Multiple algorithms have been proposed to locate the gas source within a known environment, ranging from bio-inspired to probabilistic ones. However, their application to real-world conditions still remains a major issue due to the great difficulties those scenarios bring, among others, the common presence of obstacles which hamper the movement of the robot and notably ncrease the complexity of the gas dispersion. In this work, we consider a plume tracking algorithm based on the well-known silkworm moth strategy and analyze its performance when facing different realistic environments characterized by the presence of obstacles and turbulent wind flows. We rely on computational fluid dynamics and the open source gas dispersion simulator GADEN to generate realistic gas distributions in scenarios where the presence of obstacles breaks down the ideal downwind plume. We first propose some modifications to the original silkworm moth algorithm in order to deal with the presence of obstacles in the environment (avoiding collisions) and then analyze its performance within four challenging environments.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Proyecto de excelencia de la Junata de Andalucia TEP2012-53

Integrating Olfaction in a Robotic Telepresence Loop

In this work we propose enhancing a typical robotic telepresence architecture by considering olfactory and wind flow information in addition to the common audio and video channels. The objective is to expand the range of applications where robotics telepresence can be applied, including those related to the detection of volatile chemical substances (e.g. land-mine detection, explosive deactivation, operations in noxious environments, etc.). Concretely, we analyze how the sense of smell can be integrated in the telepresence loop, covering the digitization of the gases and wind flow present in the remote environment, the transmission through the communication network, and their display at the user location. Experiments under different environmental conditions are presented to validate the proposed telepresence system when localizing a gas emission leak at the remote environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Improvement of the sensory and autonomous capability of robots through olfaction: the IRO Project

Proyecto de Excelencia Junta de Andalucía TEP2012-530Olfaction is a valuable source of information about the environment that has not been su ciently exploited in mobile robotics yet. Certainly, odor information can contribute to other sensing modalities, e.g. vision, to successfully accomplish high-level robot activities, such as task planning or execution in human environments. This paper describes the developments carried out in the scope of the IRO project, which aims at making progress in this direction by investigating mechanisms that exploit odor information (usually coming in the form of the type of volatile and its concentration) in problems like object recognition and scene-activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decisionmaking processes. The results of the IRO project have improved the robot capabilities in terms of efciency, autonomy and usefulness.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Analyzing interference between RGB-D cameras for human motion tracking

Multi-camera RGB-D systems are becoming popular as sensor setups in Computer Vision applications but they are prone to cause interference between them, compromising their accuracy. This paper extends previous works on the analysis of the noise introduced by interference with new and more realistic camera configurations and different brands of devices. As expected, the detected noise increases as distance and angle grows, becoming worse when interference is present. Finally, we evaluate the effectiveness of the proposed solutions of using DC vibration motors to mitigate them. The results of this study are being used to assess the effect of interference when applying these setups to human motion tracking.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Plan Propio de Investigación de la UMA. Junta de Andalucía, proyecto TEP2012-53

Robotic Gas Source Localization with Probabilistic Mapping and Online Dispersion Simulation

Gas source localization (GSL) with an autonomous robot is a problem with many prospective applications, from finding pipe leaks to emergency-response scenarios. In this work we present a new method to perform GSL in realistic indoor environments, featuring obstacles and turbulent flow. Given the highly complex relationship between the source position and the measurements available to the robot (the single-point gas concentration, and the wind vector) we propose an observation model that derives from contrasting the online, real-time simulation of the gas dispersion from any candidate source localization against a gas concentration map built from sensor readings. To account for a convenient and grounded integration of both into a probabilistic estimation framework, we introduce the concept of probabilistic gas-hit maps, which provide a higher level of abstraction to model the time-dependent nature of gas dispersion. Results from both simulated and real experiments show the capabilities of our current proposal to deal with source localization in complex indoor environments. To the best of our knowledge, this is the first work in olfactory robotics that doesn't make simplistic assumptions about environmental conditions like operating in open spaces and/or having an unrealistic laminar flow wind